PROJECT SUMMARY Chemical risk assessment has been widely applied in chemical industry as a necessary step to get new commercial chemicals registered, and in governmental agencies as a critical procedure to evaluate the toxicity of chemicals in order to properly regulate them to protect human health and the environment. The Lautenberg Chemical Safety Act further strengthens the importance of chemical risk assessment on both regulatory and industrial sides. The acceptance of the benchmark dose (BMD) modeling method to replace the traditional No or Lowest Observed Adverse Effect Level (NOAEL/LOAEL) approach as a default method for dose-response assessment - a key component in quantitative risk assessment - is an important step forward in analyzing and interpreting dose-response data. The BMD method has a number of important advantages over the traditional approach, however, the substantial potentials of the BMD method have been significantly limited by current practices and outdated dose-response modeling strategies represented by existing software, such as US EPA's BMDS and RIVM's PROAST software. Therefore, in this STTR project, we will explore and demonstrate the feasibility and credibility of integrating existing toxicological information into dose-response modeling for BMD estimation through a web-based Bayesian BMD modeling system. To accomplish this objective, two specific aims will be pursued: (1) develop an online dose-response modeling system with the capability to use toxicologically plausible informative priors for parameters to model common endpoints; and (2) demonstrate the utility of employing toxicology-based informative prior in enhancing the precision of BMD estimates and reducing the number of animals used in toxicity studies. The three-person team, including the project PI, COO of Dream Tech and an industry expert, will utilize the I-Corp program to discover potential customers of the dose-response modeling system being developed and develop a viable business plan to commercialize it in the next phase. The success of this project may revolutionarily change how dose-response modeling is conducted in chemical risk assessment and other relevant fields (e.g., pre-clinical evaluation in drug development), and create new horizons of research.This innovative strategy will have significant impact on chemical safety evaluation and regulation which is critical to protect hundreds of millions of people's health from chemical exposure.